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Data Scientist

Experis
United States
14 days ago
Apply on arc.dev
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Role details

Contract type
Permanent contract
Employment type
Part-time (≤ 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Languages
English
Job source
arc.dev

Tech stack

Amazon Web Services Continuous Integration Data Vault Modeling R (Programming Language) Python (Programming Language) SQL Databases Data Processing Cloud Platform System Machine Learning Operations Data Pipelines Databricks

Job description

  • Design, develop, and maintain scalable data science solutions and models;
  • Work within Databricks environments for data processing and analytics;
  • Develop and optimize data pipelines using SQL, Python, and R;
  • Contribute to CI/CD processes for data workflows and model deployment;
  • Collaborate on cloud-based data platforms (AWS preferred);
  • Apply and implement data modeling methodologies (Kimball, Inmon, Data Vault).

Requirements

  • 5+ years of professional experience as a Data Scientist;
  • Strong hands-on experience with: SQL Python R;
  • Solid experience with Databricks;
  • Experience working with cloud platforms (AWS preferred; others accepted);
  • Strong understanding of data modeling methodologies (Kimball, Inmon, Data Vault);
  • Experience with CI/CD tools and practices;
  • English proficiency level B2 or higher.
  • The candidate must reside and work in Portugal.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

Moments

Explore playlists

6:08 min

Applying software engineering environments and testing to data pipelines

Matthias Niehoff Matthias Niehoff · World Congress 2024

2:27 min

Managing traffic and tracking costs with Databricks Unity Catalog

Viktoria Semaan Viktoria Semaan · World Congress 2026 Europe

1:14 min

Evolution of distributed SQL database architectures

Wei Hu Wei Hu · World Congress 2024

2:01 min

Executing remote data exploration and model training

Mingshen Sun Mingshen Sun · World Congress 2024

47 sec

Building modern data pipelines for legacy exports

Dr. Alexander Wachtel Dr. Alexander Wachtel +1 · World Congress 2025

2:40 min

Automating self-service workspaces and data annotation pipelines

Kapil Gupta Kapil Gupta · World Congress 2025

Videos

See all
Data Science in Retail thumbnail
58:21
LIVE • over 3 years ago

Data Science in Retail

Julian Joseph

Why and when should we consider Stream Processing frameworks in our solutions thumbnail
30:51
World Congress 2024 • about 2 years ago

Why and when should we consider Stream Processing frameworks in our solutions

Soroosh Khodami

Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source thumbnail
29:50
World Congress 2026 Europe • 3 months ago

Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source

Viktoria Semaan

Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases thumbnail
32:46
World Congress 2024 • about 2 years ago

Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases

Wei Hu

Implementing continuous delivery in a data processing pipeline thumbnail
34:00
LIVE • almost 6 years ago

Implementing continuous delivery in a data processing pipeline

Álvaro Martín Lozano

Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases thumbnail
28:41
World Congress 2025 • about 1 year ago

Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases

Wei Hu

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